The year 2023 marked a significant surge in the exploration of applying large language
model chatbots, notably Chat Generative Pre‐trained Transformer (ChatGPT), across …

Recent advancements in large language models (LLMs) have achieved promising
performances across various applications. Nonetheless, the ongoing challenge of …

In this work we will show that language models with less than one billion parameters can be
used to translate natural language to SPARQL queries after fine-tuning. Using three different …

The integration of Large Language Models (LLMs) with Knowledge Graphs (KGs) offers
significant synergistic potential for knowledge-driven applications. One possible integration …

In this paper, we focus on the task of exploiting the capabilities of Large Language Models
(LLMs) to generate SPARQL Queries for answering natural questions over cultural …

Efficiently answering questions over complex, domain-specific knowledge graphs remain a
substantial challenge, as large language models (LLMs) often lack the logical reasoning …

Large Language Models (LLMs) have demonstrated remarkable capabilities in natural
language understanding and generation. However, they often struggle with complex …

Adopting Knowledge Graphs (KGs) as a structured, semantic-oriented, data representation
model has significantly improved data integration, reasoning, and querying capabilities …

We present LinkQ, a system that leverages a large language model (LLM) to facilitate
knowledge graph (KG) query construction through natural language question-answering …

Customizing Large Language Models (LLMs) for specific tasks demands high-quality,
domain-specific datasets. Existing solutions often struggle with extracting meaningful and …